The research studies how human-AI cooperative strategies transform logistics by analyzing their impact on public management processes and job definition. The rapid advancement of artificial intelligence technology selects logistics as a foundational field which utilizes machine learning alongside IoT to enhance operational capability through cost management and procedure optimization. A multiple regression analysis explores human-AI collaboration dynamics and their association with technological readiness along with workforce skills and economic environments and regulatory frameworks and organizational structures. Data collection involved 120 participants from policymaking sectors combined with industry leaders and AI specialists along with academics and labor representatives. This approach provided insights into all crucial collaborative factors. The analysis reveals that technological readiness strength and workforce skills power human-AI collaboration because these elements explain 78.2% of measurable variables. The research findings are limited by its sole focus on Morocco as well as the absence of either qualitative or longitudinal data analysis methods. To achieve sustainable AI adoption in logistics operations the recommendations focus on funding digital infrastructure implementation along with workforce education plus supportive regulatory environments and developing public–private partnerships which will drive inclusive deployment of AI technologies. Research findings from this study can serve as a starting point to develop strategies that improve both efficiency and ethical execution of human-AI working partnerships across the globe.